What is this?
A curated study guide and resource collection for machine learning interviews at FAANG-level companies, written by someone who received offers from Google, LinkedIn, Snap, Coupang and StitchFix.
A curated study guide and resource collection for machine learning interviews at FAANG-level companies, written by someone who received offers from Google, LinkedIn, Snap, Coupang and StitchFix.Is this a course, a book, or just a list of links?It's a GitHub repo organized as a study plan with topic tables and links to external articles, papers, courses and a separate paid book/course, not a standalone app or tutorial itself.
It's a GitHub repo organized as a study plan with topic tables and links to external articles, papers, courses and a separate paid book/course, not a standalone app or tutorial itself.How is the content organized and where should I start?Start from the 'Getting Started' table which links to a study guide, ML system design usecases, a quiz, and a one-week-before-onsite checklist; topics are broken into LeetCode, SQL, programming, statistics, ML/DL fundamentals and ML system design sections.
Start from the 'Getting Started' table which links to a study guide, ML system design usecases, a quiz, and a one-week-before-onsite checklist; topics are broken into LeetCode, SQL, programming, statistics, ML/DL fundamentals and ML system design sections.Do I need a coding background or just ML theory?Both: the plan expects coding practice via LeetCode (though it notes not all companies require it), SQL, and programming language fundamentals (Java, Python GIL/concurrency) alongside ML/DL theory and statistics.
Both: the plan expects coding practice via LeetCode (though it notes not all companies require it), SQL, and programming language fundamentals (Java, Python GIL/concurrency) alongside ML/DL theory and statistics.Is LeetCode practice mandatory for every ML interview covered here?No, the author explicitly states many companies skip LeetCode-style coding rounds, so that section can be deprioritized depending on your target companies.
No, the author explicitly states many companies skip LeetCode-style coding rounds, so that section can be deprioritized depending on your target companies.Who is this guide meant for?Machine learning engineers and data scientists preparing for interviews at big tech companies, from junior to experienced candidates.
Machine learning engineers and data scientists preparing for interviews at big tech companies, from junior to experienced candidates.Does it cover ML system design case studies?Yes, it links to real-world system design examples like YouTube/TikTok recommendations, Airbnb search ranking, Uber Eats delivery optimization, LinkedIn feed ranking and ad click prediction.
Yes, it links to real-world system design examples like YouTube/TikTok recommendations, Airbnb search ranking, Uber Eats delivery optimization, LinkedIn feed ranking and ad click prediction.Is there a paid component to this?Yes, the author also sells a separate 'Machine Learning System Design' course (available on educative.io and interviewquery.com) and an ML interviews book on Amazon, while the repo itself is free.
Yes, the author also sells a separate 'Machine Learning System Design' course (available on educative.io and interviewquery.com) and an ML interviews book on Amazon, while the repo itself is free.What ML fundamentals topics are covered?Logistic regression, decision trees/random forests, boosting, K-means, PCA, SMOTE, and discriminative vs generative models, several with from-scratch implementation exercises in numpy.
Logistic regression, decision trees/random forests, boosting, K-means, PCA, SMOTE, and discriminative vs generative models, several with from-scratch implementation exercises in numpy.Are there real testimonials from people who got offers using this?Yes, the README includes quotes from candidates at Amazon, Facebook, NVIDIA, Microsoft and Intel who credit the repo's quizzes and summaries for their interview prep.
Yes, the README includes quotes from candidates at Amazon, Facebook, NVIDIA, Microsoft and Intel who credit the repo's quizzes and summaries for their interview prep.What are similar projects?interview, system-design-notes, Awsome-Front-End-learning-resource, LeetCode-Questions-CompanyWise, hello-algorithm, tech-interview-handbook, system-design-interview, leetcode-company-wise-problems
interview, system-design-notes, Awsome-Front-End-learning-resource, LeetCode-Questions-CompanyWise, hello-algorithm, tech-interview-handbook, system-design-interview, leetcode-company-wise-problemsWhich topics is it in?leetcode, job-search, system-design, study-guide, interview-questions, interview, interview-preparation, career, data-science, beginner-friendly, guide, learning-resources
leetcode, job-search, system-design, study-guide, interview-questions, interview, interview-preparation, career, data-science, beginner-friendly, guide, learning-resources